= Libre Software in Africa
:author: Benson Muite
:encoding: utf-8
:lang: en
:rev: 0.5.0
:revdate: 2023-03-18
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:stylesheet: slides.css
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[#0] 
== Libre Software in Africa
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[discrete]
=== Benson Muite

[discrete]
==== https://notabug.org/tuvutepamoja

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[#1]
== Outline
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* Background
* Digitization and Libre Software
* Language Data, Machine Learning and Privacy

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[#2]
== Introduction
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* Africa
** 1.39 billion people <<WEA>>
** $2260 Nominal GDP per capita <<WEA>>
** 3.9% Real Economic GDP growth rate <<WEA>>
** 10.7% of households have a computer <<ITUFF19>>

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[#3]
== Overview of Internet Connectivity
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* 0.4 fixed broadband internet subscriptions per 100 people <<ITUFF19>>
* 34.8 active mobile internet subscriptions per 100 people <<ITUFF19>>
* 17.8% of households have internet access <<ITUFF19>>

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[#4]
== Percent Individuals Using the Internet
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* Percent of individuals in each country using the internet in 2021 <<ITUDH>>

image::data/ICT/PIUI_Africa.svg[Map showing percent individuals using the internet by country in Africa in 2021]

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[#5]
== Mobile Broadband Bandwidth Subscriptions
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* Mobile broadband bandwidth subscriptions per 100 people in 2021 <<ITUDH>>

image::data/ICT/MBS_Africa.svg[Map showing mobile bandwidth subscriptions by country in Africa in 2021]


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[#6]
== Fixed Broadband Bandwidth Subscriptions
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* Fixed broadband bandwidth subscriptions per 100 people <<ITUDH>>

image::data/ICT/FBS_Africa.svg[Map showing fixed broadband bandwidth subscriptions by country in Africa in 2020]

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[#7]
== Language Diversity
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* Continent with largest language diversity
* 2000-3000 languages
** Language Diversity Index <<WLDI>>

image::data/Language/LDI_Africa.svg[Language Diversity Index]

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[#8]
== Gross Domestic Product
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* Per capita GDP 2021 in US$

image::data/GDP/GDP_PCAP_Africa.svg[Map showing per capita GDP by country in Africa in 2021]

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[#9]
== Gross Domestic Product Growth Rate
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* Per capita GDP growth rate in 2021

image::data/GDP/GDP_PCAP_GROWTH_Africa.svg[Map showing per capita GDP growth rates by country in Africa in 2021]

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[#10]
== Education
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* Adult literacy rate <<WBLR>>

image::data/Education/LR_Africa.svg[Map showing percentage literacy rates by country in Africa]

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[#11]
== Infrastructure
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* Significant infrastructure investments
** Roads
** Telecommunications
* Some foreign investment to improve trade
** Natural resource extraction
** Labor

image::images/infrastructure.svg[Image of a road and a cell phone tower,200,150]

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[#12]
== Digitization Challenges
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* Local needs secondary
** Addressing local needs required for successful digitization
** Succesful adaptation of radio for information dissemination
** More needed for internet and computers
*** Due to costs, schools and internet cafes are first contact points
*** Smart phones are the secondary contact point

image::images/local.svg[Image of a confused person being greeted in English and a happy understanding person begin greeted in Igbo,300,120]

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[#13]
== Challenges of Libre Software
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* Poorly marketed
* Governance is often unclear
* Poor incorporation in legal and procurement systems
* Relatively high barriers to involvement when primary community is external
* Large time investment required to understand well

image::images/challenges.svg[Image showing advertisement of GNU on radio and a scale comparing GNU in an open box with a closed unknown box,350,200]

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[#14]
== Opportunities Provided by Libre Software
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* Auditable
* Easy to adapt and update
* Community driven learning
* Many packages that work well on limited hardware resources

image::images/community.svg[Image showing a village with 4 huts and 6 GNUs,250,250]

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[#15]
== Challenges of Mobile First
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* Low memory and low performance devices
* Privacy is challenging
* Mindset is usually that of software consumer not co-creator
* Wide variety of device capabilities
* Technological ecosystem is designed elsewhere

image::images/mobilefirst.svg[Image of a mobile phone before a laptop computer,200,150]

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[#16]
== Opportunities of Mobile First
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* Cloud can overcome some deficiencies
* Large potential user base
* Opportunity to develop new use cases - mobile money
* Can reuse old libre software designed for older computers

image::images/mobilefirst.svg[Image of a mobile phone before a laptop computer,200,150]

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[#17]
== Collecting Machine Learning Language Data
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* English, French and Arabic are dominant official languages
* Many other languages primarily used orally
* A starting point is collecting a corpus suitable for early education
* Enable translation of commonly used terms
* Enable easy engagement
* Motivates an online short story competition

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[#18]
== Evaluating Machine Learning Language Data
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* Language experts are few
* Community consensus for many languages is missing
* Use a voting system, if you submit you can rate
* Voting privacy and anonymity is challenging

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[#19]
== What Language Data Was Collected?
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* Submissions by language for the competitions

image::data/CompetitionStatistics/Submissions.svg[Stacked bar chart showing submissions in two competitions by language,400,300]

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[#20]
== Where can the Stories be Read?
<<19,←>><<21,→>>

* Countries where stories can be read

image::data/CompetitionStatistics/LanguagesInCountry.svg[Map of countries in Africa colored by the number of languages in which submitted stories can be read,500,400]

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[#21]
== Using Machine Learning Language Data
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* Language Learning Games
** https://tuvutepamoja.africa/Igbo-Wordle/
** https://tuvutepamoja.africa/Kinyarwanda-Wordle
** https://tuvutepamoja.africa/Kiswahili-Wordle
** https://tuvutepamoja.africa/Setswana-Wordle/

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[#22]
== Relevant Libre Software
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* Data collection platform https://tuvutapamoja.africa 
** Open source https://notabug.org/tuvutepamoja
** Written in PHP
** Easy to deploy on shared hosting
** Soft keyboard to enable correct orthography
** Minimize some of the privacy concerns
** Hard to find libre shared hosting

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[#23]
== Keyboards
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* Easy customization possible today
* More difficult on typewriters 
* Open source projects include
** https://keyman.com
** https://www.freedesktop.org/wiki/Software/XKeyboardConfig/
** https://github.com/eyedol/kasahorow-Keyboard-For-Android
** https://giellalt.github.io/ 

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[#24]
== Summary
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* Libre software can do well in Africa
* Largest challenges are mindset and regulation
*             አመሰግናለሁ
ﺶﻛﺭﺍ
Asante
Daalụ
Dankie
Enkosi
Godiya
Kea leboha
Mahadsanid
Murakoze
Ndatenda
Ngiyabonga
O ṣeun
Zikomo

image::images/GNUAfrica.svg[Image of red letters GNU in Africa,250,200]

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[#25]
== Acknowledgements
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 * William Agbo, Liané Van Den Bergh, Audrey Mbogho, 
 * Paulin Melatagia, Cascious Mofokeng, Afia Obinim, 
 * Itaru Ohta, Kevin Scannell, Juan Steyn, Benito Trollip, 
 * Lilian Wanzare, Constantine Yuka
 * https://www.idrc.ca/[International Research Development Center]
 * https://www.k4all.org[Knowledge for all]

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[#26]
[bibliography]
== Bibliography
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* [[[WEA]]] https://en.wikipedia.org/wiki/Economy_of_Africa[Wikipedia Economy of Africa]
* [[[WLDI]]] https://en.wikipedia.org/wiki/Linguistic_diversity_index[Wikipedia Linguistic Diversity Index]
* [[[WBLR]]] https://api.worldbank.org/v2/en/indicator/SE.ADT.LITR.ZS?downloadformat=csv[World Bank: Adult Literacy Rates]
* [[[ITUFF19]]] https://www.itu.int/en/ITU-D/Statistics/Documents/facts/FactsFigures2019.pdf[ITU Facts and Figures 2019]
* [[[ITUDH]]] https://datahub.itu.int/[ITU DataHub]
